Abstract
In this paper we present a hierarchical approach to text categorization aimed at improving the performances of the corresponding tasks. The proposed approach is explicitly devoted to cope with the problem related to the unbalance between relevant and non relevant inputs. The technique has been implemented and tested by resorting to a multiagent system aimed at performing information retrieval tasks.
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Addis, A., Armano, G., Mascia, F., Vargiu, E. (2007). Hierarchical Text Categorization Through a Vertical Composition of Classifiers. In: Basili, R., Pazienza, M.T. (eds) AI*IA 2007: Artificial Intelligence and Human-Oriented Computing. AI*IA 2007. Lecture Notes in Computer Science(), vol 4733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74782-6_64
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DOI: https://doi.org/10.1007/978-3-540-74782-6_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74781-9
Online ISBN: 978-3-540-74782-6
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